 At this table we collected the lessons and gaps on the tools and initially we understood tools as the really the, in its narrow sense as the technical software issues or tools we used. And we started off with listing the most important ones we used commonly across the four sites, being SPSS for data entry and MSLOR statistics, CS Pro is something new which has been introduced for data entry for next steps. Google Earth illustrates the spatial distribution and GPS to collect GIS information. And the lessons we learned to stress you with SPSS was that it was comparatively efficient data management compared to what other people have been using so far like Excel because it forced people into a strict format but that more training would be needed especially in the interactive data analysis and sharing of data analysis steps. Also licenses could be a problem. However it was felt that data entry and queries were more difficult than it would be with using other tools. CS Pro in comparison with even the limited use people have had that it is definitely easier for data entry, that's what it is made for, but to have a better understanding and more experience would be needed. And Google Earth, the sharing of site location info was very attractive that we could easily see where the other groups were working, but more training especially on the job would be used and there are more opportunities of Google Earth than just seeing specific points. But these points have been fairly consistently collected through GPS and the connection of GPS information to other applications was something new and something useful but it was not yet clear if all regions were doing it in the same way and it was not also clear for what were we actually doing this, how are we going to use this information just putting it into maps or using it in more quantitative analysis. We also listed a few tools which the visitors to this table thought would offer potential for more analysis are as a license free, very flexible, statistics package starter for specialized econometric analysis, RGIS for better spatial analysis, access for more efficient data management and sharing and SAS will as an alternative to the SPSS as a raw statistics package. However, we also have a group who thought that this understanding of what tools is about is to narrow, sorry, we did have overall issues on tools that training was an issue over all of these and it led to the suggestion that with all of these tools we do have specialists who have a far greater understanding and it would help the training if the members could be linked to these chapters to exchange knowledge and to give tips so that the learning is more efficient. And the big issue of data management across sites, especially as more data is gathered different types of data and different people are involved in it. That is really something that should be discussed and solved. But coming to other tools, apart from the software issues, we thought that the questionnaires and the models which at some stage have been thought to be included in the process table have not been covered properly in their technical details. So we did a bit on that. The Village Survey, the lesson was it was too long, too quantitative, placed high demands on the numerator and that's especially some of the nested tables were very difficult. But there were solutions, or which are linked in other gaps, that more training at the Village Level because most people are more familiar with household level data collection and that the formulation of these qualitative questions could have been improved to make it more useful. Village Census was pretty straightforward. Everybody was pretty happy. The way that data was collected varied a little bit over the sites but it was partly informal and partly for the formal collaborators. Household Survey, we don't have very many lessons at the moment but we do see gaps that there's more on markets, especially on the type of markets involved and also more on preferences. The finally on models, on modeling, it was felt that more interaction with the modelers would be useful to know more what they are about and not only small snippets. And the final issue was that how would the chip options, the technologies, traditional and policy options coming out of the whole study, how would they be defined that is still in the middle of care?